Homogeneous coordinates offer a robust mathematical framework for representing and executing geometric transformations in image processing, computer vision, robotics, and computer graphics. By embedding Euclidean space into a higher-dimensional projective space, they provide a unified mechanism for handling affine transformations, such as translation, rotation, scaling, and shear, as well as projective transformations like perspective projection. This study explores the practical applications of homogeneous coordinates within the MATLAB environment, leveraging its matrix manipulation capabilities to implement these transformations efficiently. Homogeneous coordinates simplify complex transformation pipelines through matrix concatenation, enabling seamless execution of combined operations while preserving computational efficiency and accuracy. Key applications demonstrated include image registration, warping, rectification, 3D modeling, and camera calibration, emphasizing their critical role in medical imaging, virtual reality, and augmented reality. MATLAB's intuitive programming environment and advanced visualization tools further enhance the accessibility and applicability of these techniques. This article provides detailed explanations, MATLAB code implementations, and visual demonstrations to bridge the gap between theoretical foundations and real-world applications, making it an invaluable resource for researchers, practitioners, and students in the fields of image processing and computer vision.